Browsing by Author "Zhao R"

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    Assessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.
    (Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine, 2024-11-29) Zeng H; Chen Q; E X; Feng Y; Lv M; Zeng S; Shen W; Guan W; Zhang Y; Zhao R; Wang S; Yu J
    Background Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) addresses uncertainties due to lung tumor dynamics. We aimed to investigate a comprehensively and systematically validated offline ART regimen with high clinical feasibility for lung cancer. Methods This study enrolled 102 lung cancer patients, who underwent kV iterative cone-beam computed tomography (iCBCT). Data collection included iCBCT and planning CT (pCT) scans. Among these, data from 70 patients were employed for training the UNet++ based deep learning model, while 15 patients were allocated for testing the model. The model transformed iCBCT into adaptive CT (aCT). Clinical radiotherapy feasibility was verified in 17 patients. The dosimetric evaluation encompassed GTV, organs at risk (OARs), and monitor units (MU), while delivery accuracy was validated using ArcCHECK and thermoluminescent dosimeter (TLD) detectors. Results The UNet++ based deep learning model substantially improved image quality, reducing mean absolute error (MAE) by 70.05%, increasing peak signal-to-noise ratio (PSNR) by 17.97%, structural similarity (SSIM) by 7.41%, and the Hounsfield Units (HU) of aCT approaching a closer proximity to pCT compared to kV iCBCT. There were no significant differences observed in the dosimetric parameters of GTV and OARs between the aCT and pCT plans, confirming the accuracy of the dose maps in ART plans. Similarly, MU manifested no notable disparities, underscoring the consistency in treatment efficiency. Gamma passing rates for intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans derived from aCT and pCT exceeded 98%, while the deviations in TLD measurements (within 2% to 7%) also exhibited no significant differences, thus corroborating the precision of dose delivery. Conclusion An offline ART regimen utilizing kV iCBCT and UNet++ based deep learning model is clinically feasible for lung cancer treatment. This approach provides enhanced image quality, comparable treatment plans to pCT, and precise dose delivery.
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    Comparative evaluation of pumice as a soilless substrate for indoor Rubus idaeus L. cultivation
    (Taylor and Francis Group on behalf of the Royal Society of New Zealand, 2024-07-21) Zhao R; Sofkova-Bobcheva S; Cartmill DL; Hardy D; Zernack A; Li M
    Pumice is an abundant natural resource in New Zealand and its application in horticulture could save significant costs. To investigate the effect of pumice substrates on raspberry growth and fruit quality, two dwarfing selections (sel.8 and sel.110) were grown hydroponically in (1) coconut coir (control); (2) pumice; (3) pumice/coir (50/50 v/v); (4) pumice/flax (50/50 v/v). Results showed that the addition of pumice to coir significantly increased bulk density, which provided better root anchor support for plants, and also increased the water holding capacity (WHC). Pure pumice had a higher bulk density and lower porosity compared to the other tested substrates, which enhanced fruit quality and yield, although the vegetative growth was slightly lower compared to the control. Mixed pumice/flax substrate had the lowest porosity and poorer WHC, resulting in inferior raspberry growth vigour and productivity. Our results furthermore suggested different substrates could affect the one-year-old cane height, crop yield and fruit characteristics. Pumice was more suitable for sel.8, while the pumice/coir mixture promoted a higher yield for sel.110. In conclusion, pumice and pumice-based mix substrates can be successfully used for hydroponic dwarfing raspberry production without compromising yield and fruit quality.
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    Genomic insights into the secondary aquatic transition of penguins
    (Springer Nature Limited, 2022-07-19) Cole TL; Zhou C; Fang M; Pan H; Ksepka DT; Fiddaman SR; Emerling CA; Thomas DB; Bi X; Fang Q; Ellegaard MR; Feng S; Smith AL; Heath TA; Tennyson AJD; Borboroglu PG; Wood JR; Hadden PW; Grosser S; Bost C-A; Cherel Y; Mattern T; Hart T; Sinding M-HS; Shepherd LD; Phillips RA; Quillfeldt P; Masello JF; Bouzat JL; Ryan PG; Thompson DR; Ellenberg U; Dann P; Miller G; Dee Boersma P; Zhao R; Gilbert MTP; Yang H; Zhang D-X; Zhang G
    Penguins lost the ability to fly more than 60 million years ago, subsequently evolving a hyper-specialized marine body plan. Within the framework of a genome-scale, fossil-inclusive phylogeny, we identify key geological events that shaped penguin diversification and genomic signatures consistent with widespread refugia/recolonization during major climate oscillations. We further identify a suite of genes potentially underpinning adaptations related to thermoregulation, oxygenation, diving, vision, diet, immunity and body size, which might have facilitated their remarkable secondary transition to an aquatic ecology. Our analyses indicate that penguins and their sister group (Procellariiformes) have the lowest evolutionary rates yet detected in birds. Together, these findings help improve our understanding of how penguins have transitioned to the marine environment, successfully colonizing some of the most extreme environments on Earth.